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A literature review of the training offered to qualifiedprescribers to use electronic prescribing systemsBrown, Clare L.; Reygate, Katie; Slee, Ann; Coleman, Jamie; Pontefract, Sarah; Bates, DavidW; Husband, Anthony; Watson, Neil; Slight, SarahDOI:10.1111/ijpp.12296
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Citation for published version (Harvard):Brown, CL, Reygate, K, Slee, A, Coleman, J, Pontefract, S, Bates, DW, Husband, A, Watson, N & Slight, S2016, 'A literature review of the training offered to qualified prescribers to use electronic prescribing systems'International Journal of Pharmacy Practice. DOI: 10.1111/ijpp.12296
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Publisher Rights Statement:This is the peer reviewed version of the following article: Brown, C. L., Reygate, K., Slee, A., Coleman, J. J., Pontefract, S. K., Bates, D. W.,Husband, A. K., Watson, N. and Slight, S. P. (2016), A literature review of the training offered to qualified prescribers to use electronicprescribing systems: why is it so important?. Int J Pharm Pract. doi:10.1111/ijpp.12296, which has been published in final form at10.1111/ijpp.12296 . This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving
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A literature review of the training offered to qualified prescribers to use 2
electronic prescribing systems: Why is it so important? 3
4
Clare Brown1,2
, Katie Reygate
3, Ann Slee
4,5, Jamie J. Coleman
5, Sarah K. 5
Thomas5, David W. Bates
6,7,8, Andrew K. Husband
1, Neil Watson
2, Sarah P. 6
Slight1,2,6
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Author affiliations: 8
1. Division of Pharmacy, School of Medicine, Pharmacy and Health, Durham 9
University, Stockton on Tees, Durham, U.K.; 10
2. Newcastle upon Tyne hospitals NHS Foundation Trust, Queen Victoria Road, 11
Newcastle upon Tyne, Tyne and Wear, U.K.; 12
3. Health Education KSS Pharmacy, Downsmere Building, Princess Royal 13
Hospital, West Sussex, U.K.; 14
4. eHealth Research Group, Centre for population health sciences, University of 15
Edinburgh, Edinburgh, U.K.; 16
5. College of Medical and Dental Sciences, University of Birmingham, 17
Edgbaston, Birmingham, U.K.; 18
6. The Center for Patient Safety Research and Practice, Division of General 19
Internal Medicine, Brigham and Women’s Hospital, Boston, MA, USA; 20
7. Harvard Medical School, 250 Longwood Ave, Boston, MA, USA; 21
8. Harvard School of Public Health, 677 Huntington Avenue, Boston, MA, USA. 22
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Correspondence to: 27
Dr. Sarah P. Slight MPharm, Ph.D, PGDip 28
School of Medicine, Pharmacy and Health, 29
Holliday Building, 30
Queen's Campus, 31
Stockton on Tees, 32
TS17 6BH 33
Tel: +44 191 334 0548 34
Fax: +44 191 334 0374 35
email: [email protected] 36
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Keywords: Education; Educational Measurement; Teaching; Electronic Prescribing; 38
Medical 39
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Word Count: 3507 41
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Abstract 47
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Objectives: A key element of the implementation and on-going use of an electronic 49
prescribing (ePrescribing) system is ensuring that users are, and remain, sufficiently 50
trained to use the system. Studies have suggested that insufficient training is 51
associated with suboptimal use. However, it is not clear from these studies how 52
clinicians are trained to use ePrescribing systems or the effectiveness of different 53
approaches. We sought to describe the various approaches used to train qualified 54
prescribers on ePrescribing systems and to identify whether users were educated 55
about the pitfalls and challenges of using these systems. 56
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Methods: We performed a literature review, using a systematic approach across three 58
large databases: Cumulative Index Nursing and Allied Health Literature (CINAHL), 59
Embase and Medline were searched for relevant English language articles. Articles 60
that explored the training of qualified prescribers on ePrescribing systems in a 61
hospital setting were included. 62
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Key Findings: Our search of ‘all training’ approaches returned 1,155 publications, of 64
which seven were included. A separate search of ‘online’ training found three relevant 65
publications. Training methods in the ‘all training’ category included clinical 66
scenarios, demonstrations and assessments. Regarding ‘online’ training approaches; a 67
team at the University of Victoria in Canada developed a portal containing simulated 68
versions of electronic health records, where individuals could prescribe for fictitious 69
patients. Educating prescribers about the challenges and pitfalls of electronic systems 70
was rarely discussed. 71
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Conclusions: A number of methods are used to train prescribers; however the lack of 73
papers retrieved suggests a need for additional studies to inform training methods. 74
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INTRODUCTION 88
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Electronic Prescribing (ePrescribing) systems have been associated with a 90
range of potential benefits over paper-based systems, particularly when implemented 91
with clinical decision support (CDS).(1-4) Benefits, including improved patient 92
outcomes, safer patient care and potential cost savings from improved formulary 93
management, by prompting clinicians to prescribe generic rather than branded 94
medications,(5) has meant that the number of ePrescribing systems (home grown and 95
commercial), implemented across a diverse range of settings is growing. The 96
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implementation of these systems in United Kingdom (U.K.) hospitals has surged and 97
is expected to continue increasing partly due, to the financial incentives offered such 98
as the National Health Service’s (NHS) Integrated Digital Care Fund, the Safer 99
Hospitals Safer Wards Fund and the recent government recommendations to 100
encourage increased productivity.(6-8) Similar increases in the use of healthcare 101
technology have also been seen in the United States, where the use of computerized 102
provider order entry (CPOE) systems has more than tripled since 2010.(9) This has 103
been largely driven by The Health Information Technology for Economic and Clinical 104
Health (HITECH) Act, which offered financial incentives to organisations that could 105
demonstrate ‘meaningful use’ of Electronic Health Records (EHRs).(10) Australian 106
government incentives, have also been associated with increased uptake of 107
computerised prescribing in primary care.(11) 108
A key element of the implementation and on-going use of an ePrescribing 109
system is ensuring that users are, and remain, sufficiently trained and competent to 110
use the system effectively. The user training should be comprehensive enough to 111
cover all aspects of how a user may need to interact with a system to undertake their 112
role, but also highlight potential pitfalls and challenges that they may encounter. 113
Organisations can learn from those who have experienced the implementation process 114
about what ‘went well’ and ‘not so well’. Ash et al. stressed the importance of 115
educating clinicians about the unintended consequences of ePrescribing systems, so 116
that clinicians do not fall into the trap of over reliance on technology, and risk patient 117
harm.(12) The number of different professionals (e.g. nurse or pharmacists) who can 118
prescribe is also expanding, thus the training provided needs to accommodate users’ 119
varying backgrounds and roles. These systems are continuously evolving and offer an 120
ever increasing range of new features thus it is important to not only consider 121
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introductory training but also the approaches used to inform existing staff about 122
system changes. Training is not sufficient to overcome poor design, but vendors 123
should be incentivised to develop systems using user-centred design principles. 124
Organisations face challenges in delivering effective training including: large 125
numbers of staff; staff resistance/availability to attend training; rotation between 126
wards and specialties; and temporary/short term staff. Little evidence has been 127
published on the training strategies used to familiarise staff with these systems, many 128
of which change following implementation through local customisation and system 129
upgrades. Online training strategies have been utilised in medical education and can 130
offer a potentially convenient and efficient way of training large numbers of 131
practitioners;(13) however, the effectiveness of this approach for users of ePrescribing 132
systems is not clear. 133
Some studies suggest that insufficient training is associated with suboptimal 134
use of a system.(14, 15) Baysari et al. found that large numbers of CDS alerts were 135
generated by the improper use of the system, leading to the production of ‘technically 136
preventable’ alerts.(14) Additionally, high override rates of CDS alerts have been 137
reported.(16) Her et al. found that almost 1 in 5 non-formulary medication alerts were 138
inappropriately overridden, thus reducing the potential for cost savings.(5) Shulman et 139
al. also found that the rate of errors made when using an ePrescribing system, 140
decreased over time, demonstrating a learning curve that had taken place.(17) Such 141
studies highlight the pitfalls of these systems and the importance of training and 142
education both in facilitating successful implementation of electronic systems and 143
averting errors. Furthermore, although there are fundamental differences between the 144
provision of healthcare services between clinical settings and countries, there are key 145
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elements of the prescribing process that all prescribers must perform, such as the 146
selection of a drug dose and frequency. 147
We conducted a literature review to describe the approaches used to train 148
qualified prescribers on ePrescribing systems in a hospital setting. We were also 149
interested in knowing whether online training approaches were used and whether 150
training covered the pitfalls and challenges of using these systems. 151
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METHODS 153
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Inclusion and Exclusion Criteria 155
Articles that explored the training of qualified prescribers (including medical 156
and non-medical practitioners) on ePrescribing systems in a hospital setting were 157
included. We chose to focus on the training of qualified and practicing prescribers due 158
to the specific challenges associated with training large groups of busy clinicians, 159
which can be different to the challenges faced with training undergraduate students in 160
a more ‘relaxed’ environment. We were interested in the types of training approaches 161
used, the relative effectiveness of any specific approach (if discussed), and any 162
challenges encountered. Studies that explored training of undergraduate medical 163
students, training of clinical skills other than prescribing, or the use of ePrescribing or 164
EHRs in medical education (e.g., to enable students to monitor patient progress) were 165
excluded (Appendix 1 and 2). Studies did not need to include a comparator group, as 166
this may have presented practical and ethical challenges to carrying out the study in a 167
hospital population. 168
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Search Strategy and Study Selection 170
Three large databases were searched including: Cumulative Index Nursing and 171
Allied Health Literature (CINAHL), Embase (OVID), and Medline (OVID). The 172
search terms used are listed in Table 1. Sets of search terms employed included 173
“Electronic Prescribing” OR “Computerized Provider Order Entry” in Set 1; and 174
“Clinical Decision Support” OR “Decision Support System” in Set 2; and “Electronic 175
Medical Record” in Set 3; and “Education Clinical” OR “Medical Education” in Set 176
4; and “Education Distance” in Set 5; and “Prescribing” in Set 6 (Table 1). These sets 177
were combined and our full search strategy for one database can be accessed in 178
appendix 3. The search was performed on the 15th
May 2015. Only papers published 179
in English were considered. A separate search, which included ‘electronic 180
prescribing’ and ‘online training’, was also conducted. We did not restrict the 181
timeframe for these searches. In addition, we searched the websites of vendors of 182
electronic prescribing systems supplied in the U.K for suggested training approaches. 183
We included all publication types (including editorials and opinion pieces). 184
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Data Extraction and Synthesis 186
All duplicate articles were removed. Titles and abstracts were initially 187
reviewed followed by the full text by one author (CLB) and any queries were 188
discussed with a further reviewer (SPS), if necessary. Reference lists were also 189
examined for additional papers. Data were abstracted onto a customised data 190
extraction sheet by one author (CLB), which included variables such as: title of the 191
study; country of origin; decision to include and justification for the choice. A 192
narrative synthesis of all eligible studies was undertaken. Papers were read and re-193
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read, and key recurring themes and sub-themes were identified iteratively from the 194
data. In keeping with the aim of this review, we focused on the types of training 195
approaches used to train qualified prescribers in the hospital setting and the 196
challenges associated with training. 197
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RESULTS 199
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The search for ‘all training’ returned a total of 1,155 publications; after 201
reviewing titles, abstracts and full texts, a total of 1,149 were excluded (Figure 1). 202
After reviewing the reference lists of the remaining publications, one further article 203
was included. A total of seven articles were included, comprising of three full text 204
publications from the US,(18-20) and two from Canada.(20, 21) The remaining two 205
articles were conference abstracts, one from the UK (22) and one from 206
Pakistan/Tanzania.(23) Further detail about the range of study types can be obtained 207
in Appendices 1 and 2. The authors of the conference abstracts were contacted and 208
asked for additional information, including (i) the type of training delivered and 209
whether online training methods were used (if unclear from the publication), (ii) 210
whether a competence assessment was used, and (iii) whether the training was 211
developed internally or by the vendor. We obtained responses from all authors apart 212
from one.(23) We decided to include the two studies by Borycki et al. and Kushniruk 213
et al., as there was potential for these training methods to be used for practicing 214
prescribers.(20, 21) 215
The separate search for the use of ‘online’ training methods returned 25 216
publications. After reviewing the titles, abstracts and full text, three relevant articles 217
were identified (Figure 2), two of which were previously identified and included in 218
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the search of “all training” approaches. The additional article found in this separate 219
‘online’ search(24) was included making eight publications in total. 220
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Traditional training approaches 222
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Typically, a variety of training methods were used such as classroom-based 224
sessions, which included ‘run through’ demonstrations and practical exercises, as well 225
as face-to-face or ward-based training facilitated by ‘super-users’ (expert staff 226
members that have received additional training). Super-users were found to play a 227
valuable role in providing ward-level support and reduce the need for costly external 228
training.(25) Tools such as e-learning packages, quick reference guides, for example a 229
list for keyboard short cuts and ‘how to’ guides, were also provided.(18, 22) Three 230
studies used traditional classroom-based learning to train users; one on a paediatric 231
intensive care unit,(22) another across an integrated delivery system(18), and a third 232
study conducted at two United States (U.S.) hospitals.(25) Users were given an 233
overview of the specific features of their system, using a combination of 234
demonstrations, lectures and practical exercises, thus allowing the users to gain 235
‘hands-on’ experience of using the system.(18, 22) In particular Bredfeldt et al. 236
encouraged staff to customise their own live version of the EHR by, for example, 237
creating preference lists, thus allowing users to experience the benefits of this 238
functionality immediately.(18) Ensuring clinicians have ample opportunities to attend 239
training was important, so weekend and out-of-hour sessions were organised in one 240
study.(25) 241
In terms of user evaluation, formal assessments, quizzes and feedback 242
methods were utilized in three studies.(18, 22, 23) Bredfeldt et al. evaluated post-243
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training performance of two skills (covered during the training session) to measure 244
the effect of training.(18) Classroom-based training and ‘hands-on’ activities were 245
found to have been associated with improved utility of certain functions.(18) 246
However, users would have appreciated more opportunities to receive training on the 247
‘live’ system and felt that the range of topics covered should be broader.(18) 248
Bredfeldt et al. also sent e-mails to users to report their usage of specific features and 249
compared their activity with that of their peers, serving to remind users of the learning 250
material and track their progress.(18) 251
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Online training approaches 253
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Web-based demonstrations were used in only one study.(23) Three papers 255
describe the work of one team, which have developed an online portal, which housed 256
a range of simulated versions of different EHRs containing electronic prescribing 257
functionality. Healthcare professional students, practicing professionals and 258
healthcare informaticians were given access to this portal where they could prescribe 259
for fictitious patients in a safe environment.(20, 21, 24) The portal also provided an 260
opportunity for users to learn about the design of different systems that influence 261
clinical practice.(20, 21, 24) 262
Evaluation of online training methods was limited. Experiences and lessons 263
learned from the University of Victoria’s EHR portal appeared to be positive, with 264
users perceiving the experience as valuable and having a greater understanding of 265
how EHR systems were to be used in practice.(20) Ayoub et al. did not specify how 266
quizzes were developed or which areas were assessed; although trainees reportedly 267
scored highly in these.(23) Jimenez highlighted the importance of providing timely 268
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feedback to users after completing exercises.(19) 269
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Clinical scenarios and exercises 271
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Two studies described using targeted clinical scenarios that focused on 273
particular problem areas to train staff. Foster et al. developed exercises based on 274
commonly encountered prescribing errors, such as the prescribing of Tazocin®
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(piperacillin-tazobactam, an antibacterial) at non-standard times.(22) Bredfeldt et al. 276
targeted training to specific clinical areas, such as pre-operative patient visits, where 277
there had been a number of support requests from existing users.(18) Developing 278
expertise-specific scenarios relevant to clinicians from different specialist areas was 279
considered important.(19, 24) 280
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DISCUSSION 282
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The papers identified a range of approaches used to train qualified prescribers, 284
including the use of ‘traditional’ training, online training, and clinical scenarios and 285
exercises. The use of a range of different approaches may appeal to individual 286
learning styles, with users appreciative of relevant and tailored clinical-scenarios in 287
particular. We chose to search for published studies in three large databases. 288
However, it is possible that studies may have been published in other databases or 289
unpublished work (e.g., reports or working papers) may exist in the grey literature. 290
We only focused on the training of qualified prescribers due to the specific 291
requirements of their training. However, we are conscious that some training 292
approaches used for other groups, such as undergraduate students, may have been 293
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potentially applicable and possibly useful. We also acknowledge that only one 294
researcher (CLB) conducted the data extraction and no quality assessment of the 295
included studies was undertaken. Notwithstanding these limitations, it is clear that 296
there is a lack of published research in this area, which needs to be addressed; 297
organisations should also share any lessons learnt from their experiences of training 298
prescribers during the implementation stage and after continued use of ePrescribing 299
systems to fill the knowledge gap.(26) 300
The papers identified outlined a number of methods used to train qualified 301
prescribers, including classroom-based sessions,(18, 22, 25) demonstrations and 302
‘hands-on’ exercises. Some studies incorporated assessment, which allowed users to 303
track their own progress and informed senior staff about those who may need further 304
assistance.(18, 22, 23) Clinical scenarios aimed at addressing commonly encountered 305
prescribing errors or frequent technical support requests were also used.(18, 22) Such 306
problem areas may reveal systems flaws that may contribute to the occurrence of 307
errors or poor usability. For instance, although ePrescribing can decrease prescribing 308
of ‘non-formulary medicines’,(27) formulary alerts are often inappropriately 309
overridden.(5) Therefore, understanding how users interact with these systems is 310
important for the development of informed training strategies. 311
This review found that combinations of different learning methods were used, 312
which appealed to the learning styles of different users. For example, Ross and 313
Banchy used a combination of one-to-one and group classroom-training sessions to 314
address the specific needs of medical staff and maximise attendance.(25) Evidence of 315
this was also apparent when training staff on other non-ePrescribing forms of 316
healthcare-information systems. For instance, McCain et al. reported how challenging 317
it was to get nurse and physician users to attend classroom-based training sessions on 318
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an EHR system (as opposed to an electronic prescribing system) due to other clinical 319
commitments. Users felt that these sessions failed to address their learning needs by 320
either being too simplistic or too advanced. This resulted in a blended learning 321
strategy being adopted that included a combination of computer-based learning 322
exercises and a training CD, which facilitated ‘self-study’ where users could train at a 323
convenient time and pace.(28) Clearly, this approach may be beneficial when training 324
prescribers on ePrescribing systems. Therefore, due to the heavy workloads and often 325
unpredictable schedules of prescribers, it would seem reasonable to suggest a training 326
approach that allows users to train at their own pace and convenience. Laramee et al. 327
found that participants preferred written guidance on how to perform tasks rather than 328
computer ‘help’ functions. Organisations should therefore consider providing a range 329
of learning tools to meet users’ needs.(28-30) Notably, we found a relatively small 330
number of studies, which have been conducted either on one particular ward or 331
organisation, thus may not be generalisable to other settings. The workforce in rural 332
or remote locations for instance, may lack sufficient resources to hire healthcare 333
informatics staff who are important for the deployment and ongoing support of 334
ePrescribing systems, therefore more targeted and accessible approaches such as 335
checklists and toolkits may be useful.(10) 336
It is likely that other training methods employed in practice are not discussed 337
in the small number of articles found in this review. Suppliers of ePrescribing systems 338
may provide a range of training options, such as workshops or e-learning; however 339
these are typically focused towards key internal staff who will disseminate training to 340
others or are primarily delivered during the implementation phase, rather than during 341
the later stages when the systems are embedding (on-going support). 342
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The use of e-learning as a method of training clinicians on an ePrescribing 343
system was considered important in the included studies.(18, 19) A study, which 344
delivered educational material primarily to nurses via an e-learning tutorial, was 345
associated with high completion rates of the training module (74% of the 2,080 346
nurses) and perceived improvements in the completeness of documentation within the 347
EHR, thus supporting this approach.(31) The American Health Information 348
Management Association (AHIMA) and the American Medical Informatics 349
Association (AMIA) developed recommendations related to workforce issues during 350
EHR implementation and suggested that a range of innovative learning techniques, 351
including electronic-methods, should be used.(26) E-learning material should be 352
engaging, potentially including interactive scenarios, simple and concise, clearly 353
specify learning outcomes, and take care to limit the amount of information 354
presented.(31) With organisations choosing to migrate from one system to another 355
(e.g., Brigham and Women’s hospital in Boston recently transitioned from a home-356
grown system to a commercial system), and clinicians often rotating between sites 357
(e.g., between a tertiary care and a community hospital) or specialities (e.g., between 358
a medical and a surgical rotation), it is important that users feel able to carry out their 359
key tasks on different systems. Tools such as the University of Victoria’s EHR portal 360
that provided users with an opportunity to train on a range of systems may be 361
particularly useful. These ‘virtual learning environments’ should replicate as much as 362
possible the interoperability issues associated with using multiple systems (e.g. failure 363
to integrate allergy information from the EHR into the ePrescribing software)(32) so 364
that prescribers are prepared for these challenges. The importance of intra-system 365
interoperability, and the need to improve the transfer and use of information between 366
systems is well-recognised in the literature.(33, 34) 367
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Training specifically aimed towards educating prescribers about the 368
challenges and pitfalls of ePrescribing was rarely discussed. However, studies 369
frequently include education and training as a solution to some of “the issues” 370
encountered, or as an explanation for why users fail to use the system as intended.(14, 371
35-37) Sittig et al. made specific recommendations, such as, providing adequate 372
training opportunities for clinicians to experience the system before implementation, 373
potentially enforcing a minimum level of training before use of the system is 374
authorised. They also proposed that organisations deliver ‘walk-throughs’ of the 375
different processes for specific clinical staff.(36) This supports the studies by Foster et 376
al. and Bredfeldt et al, which highlight the need to tailor the clinical scenarios and 377
content of training to the role, expertise and tasks performed by the user.(18, 22, 38, 378
39) Training approaches should encompass both procedural tasks (e.g., prescribing) 379
and cognitive tasks (e.g., interpreting CDS alerts) so that prescribers realise the full 380
potential of the system.(38) Importantly, prescribers should be able to identify and 381
address gaps in their own knowledge;(26) learning outcomes can provide a 382
benchmark for users to judge themselves against.(40) Alongside training, it is 383
important for system developers to improve the design and usability of ePrescribing 384
and CDS systems. Increasing CDS alert specificity and sensitivity to produce more 385
‘patient-centred’ recommendations is likely to reduce the impact of alert-fatigue and 386
improve patient outcomes.(41, 42) Implementation is costly,(3) therefore the effect of 387
interventions, should be evaluated to inform practice. 388
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CONCLUSION 390
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Organisations are currently using a range of learning methods to train 392
qualified prescribers to use electronic systems. Online learning may facilitate the 393
training for many users. However, the lack of papers retrieved suggests a need for 394
additional studies to inform training and assessment methods. Finally, further research 395
should explore the best way of training users about the pitfalls and challenges 396
associated with electronic systems. 397
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Competing Interests Statement: The authors have no competing interests to declare. 399
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34 Poon EG et al. Overcoming barriers to adopting and implementing computerized 495 physician order entry systems in US hospitals. Health Aff. 2004 Jul-Aug;23(4):184-496
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40 Biggs J. Aligning teaching for constructing learning. The Higher Education 512
Academy. 2003:p1-4. 513 41 Coleman JJ et al. On the alert: future priorities for alerts in clinical decision 514 support for computerized physician order entry identified from a European workshop. 515 BMC Med Inform Decis Mak. 2013;13:111. 516
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Table 1: Search Terms 534
21
21
535 Set 1
(Electronic
Prescribing)
Set 2
(Clinical
Decision
Support)
Set 3
(Electronic
Medical
Record)
Set 4
(Education
Clinical)
Set 5
(Education
Distance)
Set 6
(Prescriber
(Included in
Embase Search
Only))
Computerized
prescriber order
entry
Computerized
provider order
entry
Electronic
physician order
entry
Electronic order
entry
Electronic
prescribing
Electronic
prescription
Computerized
physician order
entry
CPOE
Computerized
order entry
Medical order
entry systems
Clinical
decision
support
Decision
support
system
CDS
Drug
therapy,
computer
assisted
Electronic
medical
record/
Electronic
health record
Electronic
patient record
Education
Clinical
education
Training
Course
Competence
Medical
education
Clinical
competence
Competence
assessment
Prescriber
training
Prescriber
assessment
Education
Distance
Distance
learning
Educational
non-
traditional
(CINAHL
only)
Prescribed
Prescribing
Prescription